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This publication provides an overview of additive manufacturing techniques including Inkjet, 3D and 4D printing methods. The strengths, opportunities and advantages of this array of manufacturing techniques are evaluated at different scales. We discuss first the applicability of additive manufacturing techniques at the device scale including the development of origami inspired tunable RF structures as well as the development of skin-like conformal, flexible systems for wireless/IoT, Smartag and smart city applications. We then discuss application at the package scale with on package printed antennas and functional packaging applications. Following this, there is a discussion of additive manufacturing techniques in applications at the die scale such as 3D printed interconnects. The paper is concluded with an outlook on future advancements at the component scale with the potential for fully printed passive components.

This publication considers the use of a variety of additive manufacturing techniques in the development of wireless modules and sensors. The opportunities and advantages of these manufacturing techniques are explored from an application point of view. We discuss first the origami (4D-printed) structures which take advantage of the ability to alter the shape of the inkjet-printed conductive traces on the paper substrate to produce a reconfigurable behavior. Next, focus is shifted towards the use of additive manufacturing technology to develop skin-like flexible electrical system for wireless sensing applications. We then discuss the development of a fully flexible energy autonomous body area network for autonomous sensing applications, the system is fabricated using 3D and inkjet printing techniques. Finally, an integration of inkjet and 3D printing for the realization of efficient mm-wave 3D interconnects up to 60GHz is discussed.

Tremendous reforms and dramatic changes are taking place in Chinese higher education in order to adjust to the transition from planned economy to market economy. This is especially true of architecture engineering. With unprecedented emphasis attached, cultural quality inclusion in the curriculum has been considered as important as specialty training. With the cultivation of solid foundation, great adaptability and strong ability as the desired goals of engineering education, the training system of engineers and technicians which is featured by particular periods, stages and modules has been set up while innovative spirits and practical abilities have been more and more attended to. However, the tasks of reforming teaching materials, curricular system and teaching methods remain severe.

A prerequisite for a synthetic description of the learning and memory (LM), neural bases is a model of the brain. The model we have adopted is based on functional anatomy and consists of three interacting systems. The first, R for representation, is made of the neurons which code sensory information or motor programs with the highest precision. The second, A for activation, comprises the neurons which are most directly involved in arousal and motivation. The third system, S for supervision, controls goal-directed behaviors. The best illustration of its functions is the “voluntary act” in humans: it involves a representation of a goal and of the appropriate strategies, the evaluation of the results and the correction of errors.

The memory system is not an anatomically separate entity but a set of interactions between R, A and S. In these interactions, the three systems have different though complementary functions. R is mainly involved in encoding and storage. S plays a role in encoding and retrieval through the control of attention and cognitive strategies. Structures of A, which modulate R and S activities, are involved in all stages of memory processes. Different types of LM set into play different types of interactions between R, A and S.

Within this general scheme, we considered data from different levels of organization, from the whole brain to the molecule, through intermediates such as small networks (for example, the cortical column). Finally, an attempt is made at defining the perspectives for future research. Among its main objectives are the integration of LM bases in the neurobiology of the whole behavior, the genetic and developmental factors, new therapies for improving memory in aged and demented people, the design of formalisms able to represent large-scale neural networks.